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Record W3088024867 · doi:10.21037/lcm-20-34

A Narrative review of scientific validation of gold- and silver-based Indian medicines and their future scope

2020· review· en· W3088024867 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueLonghua Chinese Medicine · 2020
Typereview
Languageen
FieldMedicine
TopicPhytochemicals and Medicinal Plants
Canadian institutionsConcordia University
Fundersnot available
KeywordsScope (computer science)NarrativeNarrative reviewEngineering ethicsTraditional medicinePsychologyMedicineEngineeringComputer scienceArtLiteraturePsychotherapist

Abstract

fetched live from OpenAlex

Metals are incinerated along with plant extracts and used as oral drugs in the Indian traditional medicines, such as Ayurveda and Siddha. Gold and silver ashes are predominantly used in cancer therapy and for treating neuronal disorders. Since the beginning of the nano-era, these ashes were investigated for their characteristics, especially the size of the particles. Numerous hypotheses were advanced to repurpose them as nanomedicines. During the last two decades, several studies were conducted studying the correlation of the particle size and the therapeutic effects. Here, we discuss the processes used to prepare gold and silver ash that result in the formation of nano- and micro-scale particles. Further, we review recent works on the ashes using modern tools and their scope, in nanomedicine. We emphasize the need to generate experimental data of high-quality to reinforce the scientific validation of these traditional medicines.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.478
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0060.000
Bibliometrics0.0000.002
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.024
GPT teacher head0.340
Teacher spread0.315 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it